Journal:Can a byte improve our bite? An analysis of digital twins in the food industry
| Full article title | Can a byte improve our bite? An analysis of digital twins in the food industry |
|---|---|
| Journal | Sensors |
| Author(s) | Henrichs, Elia Noack, Tanja; Piedrahita, Ana María Pinzon; Salem, María Alejandra; Stolz, Johnathan; Krupitzer, Christian |
| Author affiliation(s) | University of Hohenheim |
| Primary contact | christian dot krupitzer at uni-hohenheim dot de |
| Editors | Tiwari, Ashutosh |
| Year published | 2022 |
| Volume and issue | 22(1) |
| Article # | 115 |
| DOI | 10.3390/s22010115 |
| ISSN | 1424-8220 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://www.mdpi.com/1424-8220/22/1/115/htm |
| Download | https://www.mdpi.com/1424-8220/22/1/115/pdf (PDF) |
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This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
The food industry faces many challenges, including the need to feed a growing population, manage food loss and waste, and improve inefficient production systems. To cope with those challenges, digital twins—digital representations of physical entities created by integrating real-time and real-world data—seem to be a promising approach. This paper aims to provide an overview of digital twin applications in the food industry and analyze their challenges and potentials. First, a literature review is executed to examine digital twin applications in the food supply chain. The applications found are classified according to a taxonomy, and key elements to implement digital twins are identified. Further, the challenges and potentials of digital twin applications in the food industry are discussed. This survey reveals that application of digital twins mainly target the production (i.e., agriculture) or food processing stages. Nearly all applications are used for monitoring and many for prediction. However, relatively few focus on the integration of digital twins in systems for developing autonomous control or providing recommendations to humans. The main challenges of implementing digital twins are combining multidisciplinary knowledge and providing enough data. Nevertheless, digital twins provide huge potentials, e.g., in determining food quality, ensuring traceability, or designing personalized foods.
Keywords: digital twins, food industry, food supply chain, cyber–physical systems, sensors, internet of things, survey
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This presentation is faithful to the original, with only a few minor changes to presentation and updates to spelling and grammar. In some cases important information was missing from the references, and that information was added.
